What you receive
- Entity map for brand, people and services
- Review of company, team and author signals
- Source standard for specialist content
- Analysis of relevant external mentions
- Schema and consistency review
What a clear entity means in practice
A brand should be named and described consistently and connected to its services, people and markets. The same applies to central experts. If names, roles, profiles, publications and author information conflict, unnecessary ambiguity is created.
We therefore review company, team, author and service pages together. The aim is a structure that makes it clear who stands for which expertise, which content belongs to which service and what external evidence supports key statements.
Why sources matter more
Generative answers become more useful when claims can be grounded in traceable sources. For B2B topics, primary sources, official documentation, industry associations, company disclosures, market reports and credible first-party data are especially useful.
This does not mean adding as many outbound links as possible. Sources should support specific claims. Our own interpretation remains clearly separated from external facts, making content easier for both humans and machines to evaluate.
External mentions as context
Owned content explains how a company positions itself. External mentions add information about how other sources place the brand or person in context. Trade media, conferences, associations, partners, customers and credible directories can therefore contribute meaningful context.
We distinguish relevance from raw link volume. A topic-specific mention with clear attribution can be more useful than dozens of generic directory links. The goal is not artificial link building but credible external grounding.
The role of structured data
Schema.org can describe people, organizations, articles, services and breadcrumbs precisely. Good structured data reflects visible content and should not invent facts that are absent from the page.
Google explicitly says no special AI markup is required for its generative search features. We therefore treat schema as clean technical description, not as a secret ranking lever for AI visibility.
Keeping entities consistent across languages
Multilingual sites may describe roles, brands and services differently in each language without changing their identity. Canonicals, hreflang, profiles and structured data should still represent the relationships correctly.
Local evidence can vary. A Brazil page needs different sources from a Germany page. The core brand and person identity stays consistent while supporting evidence changes with the market.
From analysis to action
Further AI visibility building blocks
AI Search for B2B
AI search is not a separate universe from SEO. Visibility still depends on indexable pages, clear information architecture, useful content, credible evidence and consistent expertise. The difference is that systems can retrieve sources across multiple subquestions and comparison tasks.
ChatGPT Visibility for B2B
There is no guaranteed placement in ChatGPT Search. A strong foundation includes public pages, access for OAI-SearchBot, clear information structure, useful content and externally credible expertise. The goal is visibility for relevant B2B questions, not merely getting the brand name mentioned.
Measuring AI Visibility in B2B
We measure AI visibility by system and query set. This combines first-party data such as Bing AI Performance and Google Search Console with documented prompts, source observation and buyer-intent classification. A single “AI visibility score” can be an internal model, but it is not objective truth.
Connecting SEO and AI Visibility
Google confirms that SEO fundamentals remain relevant for generative search features. We therefore treat AI visibility as an extension of the search and content system: the same strong pages, a broader source perspective, more complex buyer questions and system-specific measurement.
Content for AI Answer Systems
We do not use a special AI copy style. We improve information density, definitions, section clarity, primary sources, examples and internal relationships. Google continues to recommend helpful original content and says special AI files or AI-specific markup are not required for its generative search features.
Sources & current references
OpenAI — Publishers and Developers FAQ
Google Search Central — Optimizing for generative AI features
Google Search Central — AI features and your website
Bing Webmaster — AI Performance in Bing Webmaster Tools
Review your sources and entity structure
A clear entity is not created by adding as much schema markup as possible. It comes from consistent naming, unambiguous profiles, strong internal relationships, credible primary information and relevant external mentions. Structured data helps describe visible content in machine-readable form.
